基于AUPC的Q/V频段信关站上行链路优化研究  

Research on the Optimization of Q/V-band Uplink for Gateway Stations Based on AUPC

作　　者：蓝廷帅 王彬 LAN Tingshuai;WANG Bin(Chongqing Satellite Network System Co.,Ltd.,Chongqing 401120,China)

机构地区：[1]重庆星网网络系统研究院有限公司,重庆401120

出　　处：《通信技术》2025年第1期31-38,共8页Communications Technology

摘　　要：为了探究自适应上行功率控制(Adaptive Uplink Power Control,AUPC)在Q/V频段卫星信关站链路中的应用与优化,针对Q/V频段的高频特性,以及卫星通信面临严重的路径损耗和天气衰减的问题,特别是雨衰的影响,通过仿真对比传统AUPC、比例-积分-导数(Proportion Integral Differential,PID)控制和基于机器学习的AUPC这3种功率控制算法。结果表明,基于机器学习的AUPC算法在复杂和极端天气条件下预测表现最佳,能够有效预测链路变化并提前调整功率,保证了链路稳定性和通信质量。此外,还提出了基于多频段链路冗余和动态功率调节的优化策略,以期为高频段卫星通信系统提供重要的技术参考。This paper explores the application and optimization of AUPC(Adaptive Uplink Power Control)in Q/V-band satellite gateway links.Due to the high-frequency characteristics of the Q/V band and the severe path loss and weather attenuation problems faced by satellite communications,especially the effect of rain attenuation,three power control algorithms,namely,conventional AUPC,PID(Proportion-IntegralDifferential) control,and machine learning-based AUPC,are compared through simulation.Experimental results indicate that the machine learning-based AUPC algorithm has the best predicting performance under complex and extreme weather conditions,and can effectively predict link changes and adjust the power in advance to ensure link stability and communication quality.The paper also proposes optimization strategies based on multi-band link redundancy and dynamic power adjustments,providing important technical references for future high-frequency satellite communication systems.

关 键 词：自适应功率控制 Q/V频段 机器学习 雨衰 上行链路 

分 类 号：V556[航空宇航科学与技术—人机与环境工程]